Systems | Development | Analytics | API | Testing

Control the spend and usage of your AI testing agents | SmartBear BearQ

Worried an AI teammate could rack up a surprise bill? In this video, you’ll learn how SmartBear BearQ gives you real governance over AI testing spent – built with pre-baked monthly limits, so your team always knows what to expect before a single agent gets to work.

Real Estate Data Enablement: Make Property Data Usable for AI, Reporting, and Automation

Which properties in your portfolio are becoming less profitable, and why? A reliable answer usually means pulling lease and occupancy data from the property management system (PMS), operating costs from accounting, maintenance records from a third platform, and rent comparables from outside the company. Some of it lives only in a spreadsheet one analyst maintains. The answer can take days, and two teams can come back with different numbers. Large real estate companies rarely lack software or data.

The eMudhra certificate compromise: how it affects Bitrise users

On October 17, 2026, the developer world learned that the private keys of eight intermediate certificate authority (CA) certificates from eMudhra had been compromised. In this article, I’ll explain how that affects the Bitrise environment powering your Bitrise CI jobs, Build Hub runners, and Remote Developer Environments.

How AI Is Changing the Role of the Modern QA Engineer

If you started in quality engineering decades ago, your whole mental model was forged in deterministic logic: assert(actual === expected). You took a business requirement specification, mapped out boundary values, wrote explicit test steps in TestRail or Jira, and automated them in Selenium, Cypress, or Playwright. In traditional QA testing, if an input of 2 + 2 yielded anything other than 4, you opened a severity-1 blocker, attached the stack trace, and kicked the build back to the developers.

AI Workspace + Cursor: Generating a consistent test base from your code

Prompting your agentic IDE to write tests gives you different steps and different results every time. The result is inconsistent and low-quality test cases. Combine AI Workspace's agentic workflows with your Cursor IDE to generate a consistent, reusable test base straight from your code repository. In this walkthrough, Product Marketing SVP Ryan Yackel will show how Tricentis generates test cases from a GitHub repo, stores them in qTest, and runs tests against a desktop application.

Hot Sauce Releases - Better Together: Meet Sauce Labs AURA

AI-generated code is growing exponentially. Verified releases are growing linearly. AURA (AI-Unified Release Assurance) is Sauce Labs' agentic AI platform that closes that gap: authoring, running and analyzing tests at AI speed, with human oversight, inside the tools your team already uses. In this on-demand session, Steven Spadaccini and Trent Yoxall walk one control plane through four doors.